| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 97.08% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1712 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 26.99% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1712 | | totalAiIsms | 25 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | | | 20 | |
| | highlights | | 0 | "crystal" | | 1 | "velvet" | | 2 | "tracing" | | 3 | "chill" | | 4 | "calculating" | | 5 | "stark" | | 6 | "flicked" | | 7 | "fascinating" | | 8 | "glint" | | 9 | "clandestine" | | 10 | "silence" | | 11 | "weight" | | 12 | "dancing" | | 13 | "porcelain" | | 14 | "calculated" | | 15 | "race" | | 16 | "sense of" | | 17 | "pristine" | | 18 | "firmly" | | 19 | "unspoken" | | 20 | "reminder" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 0 | | maxInWindow | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 100 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 100 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 148 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 52 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1695 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 64 | | wordCount | 1093 | | uniqueNames | 21 | | maxNameDensity | 1.83 | | worstName | "Julian" | | maxWindowNameDensity | 4 | | worstWindowName | "Julian" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Golden | 2 | | Empress | 2 | | Soho | 1 | | London | 1 | | Cardiff | 1 | | University | 1 | | Cathays | 1 | | Park | 1 | | Savile | 1 | | Row | 1 | | Bute | 1 | | Building | 1 | | Rory | 12 | | Julian | 20 | | Roath | 1 | | Paddington | 1 | | Station | 1 | | Evan | 2 | | Silas | 11 |
| | persons | | 0 | "Rory" | | 1 | "Julian" | | 2 | "Evan" | | 3 | "Silas" |
| | places | | 0 | "Raven" | | 1 | "Soho" | | 2 | "London" | | 3 | "Cardiff" | | 4 | "Cathays" | | 5 | "Park" | | 6 | "Bute" | | 7 | "Building" | | 8 | "Roath" | | 9 | "Paddington" |
| | globalScore | 0.585 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 80 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1695 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 148 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 90 | | mean | 18.83 | | std | 17.64 | | cv | 0.936 | | sampleLengths | | 0 | 93 | | 1 | 15 | | 2 | 35 | | 3 | 37 | | 4 | 51 | | 5 | 22 | | 6 | 1 | | 7 | 69 | | 8 | 1 | | 9 | 12 | | 10 | 6 | | 11 | 47 | | 12 | 10 | | 13 | 28 | | 14 | 5 | | 15 | 9 | | 16 | 3 | | 17 | 2 | | 18 | 46 | | 19 | 4 | | 20 | 7 | | 21 | 42 | | 22 | 7 | | 23 | 28 | | 24 | 10 | | 25 | 6 | | 26 | 12 | | 27 | 22 | | 28 | 14 | | 29 | 13 | | 30 | 83 | | 31 | 14 | | 32 | 3 | | 33 | 3 | | 34 | 8 | | 35 | 15 | | 36 | 10 | | 37 | 10 | | 38 | 9 | | 39 | 9 | | 40 | 16 | | 41 | 52 | | 42 | 26 | | 43 | 1 | | 44 | 10 | | 45 | 10 | | 46 | 27 | | 47 | 29 | | 48 | 16 | | 49 | 6 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 100 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 156 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 148 | | ratio | 0 | | matches | (empty) | |
| 88.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1107 | | adjectiveStacks | 2 | | stackExamples | | 0 | "small, crescent-shaped scar" | | 1 | "large, leather-bound bookshelf" |
| | adverbCount | 8 | | adverbRatio | 0.007226738934056007 | | lyAdverbCount | 3 | | lyAdverbRatio | 0.0027100271002710027 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 148 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 148 | | mean | 11.45 | | std | 7.34 | | cv | 0.641 | | sampleLengths | | 0 | 14 | | 1 | 19 | | 2 | 14 | | 3 | 18 | | 4 | 28 | | 5 | 15 | | 6 | 24 | | 7 | 11 | | 8 | 15 | | 9 | 22 | | 10 | 6 | | 11 | 10 | | 12 | 23 | | 13 | 12 | | 14 | 7 | | 15 | 7 | | 16 | 8 | | 17 | 1 | | 18 | 5 | | 19 | 11 | | 20 | 6 | | 21 | 15 | | 22 | 32 | | 23 | 1 | | 24 | 8 | | 25 | 4 | | 26 | 6 | | 27 | 14 | | 28 | 8 | | 29 | 5 | | 30 | 20 | | 31 | 10 | | 32 | 10 | | 33 | 18 | | 34 | 5 | | 35 | 9 | | 36 | 3 | | 37 | 2 | | 38 | 7 | | 39 | 15 | | 40 | 19 | | 41 | 5 | | 42 | 4 | | 43 | 7 | | 44 | 9 | | 45 | 15 | | 46 | 18 | | 47 | 7 | | 48 | 28 | | 49 | 10 |
| |
| 42.57% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.21621621621621623 | | totalSentences | 148 | | uniqueOpeners | 32 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 97 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 26 | | totalSentences | 97 | | matches | | 0 | "His hazel eyes tracked the" | | 1 | "He shook the excess water" | | 2 | "His gaze swept the dimly" | | 3 | "Her spine straightened against the" | | 4 | "Her bright blue eyes fixed" | | 5 | "He crossed the uneven floorboards." | | 6 | "His hair, once a riotous" | | 7 | "She pivoted her torso." | | 8 | "He slid a square cardboard" | | 9 | "She gave a microscopic nod." | | 10 | "He inspected the dim lighting," | | 11 | "His nose wrinkled in distaste." | | 12 | "He did not smile." | | 13 | "He had promised to keep" | | 14 | "He had promised to check" | | 15 | "He set the glass down." | | 16 | "He lifted his chin." | | 17 | "His eyes lacked the fierce," | | 18 | "His posture crumbled under the" | | 19 | "He stared at his distorted" |
| | ratio | 0.268 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 94 | | totalSentences | 97 | | matches | | 0 | "The green neon sign outside" | | 1 | "Silas leaned against the mahogany" | | 2 | "The silver signet ring on" | | 3 | "His hazel eyes tracked the" | | 4 | "Rory sat at the far" | | 5 | "The Golden Empress polyester uniform" | | 6 | "A steaming plate of pork" | | 7 | "The heavy oak door at" | | 8 | "A violent gust of London" | | 9 | "A man stepped across the" | | 10 | "He shook the excess water" | | 11 | "His gaze swept the dimly" | | 12 | "The assessment ended the moment" | | 13 | "Rory dropped her hand from" | | 14 | "Her spine straightened against the" | | 15 | "Her bright blue eyes fixed" | | 16 | "He crossed the uneven floorboards." | | 17 | "The reckless, arrogant grin from" | | 18 | "His hair, once a riotous" | | 19 | "The years had sanded away" |
| | ratio | 0.969 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 97 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 55 | | technicalSentenceCount | 2 | | matches | | 0 | "The Golden Empress polyester uniform clung to her skin, maintaining the damp chill of three hours spent dodging Soho traffic on a rusted moped." | | 1 | "The years had sanded away the rough, vibrant edges of the boy who argued constitutional law over cheap cider in Cathays Park, leaving behind a man polished, rig…" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |